Introduction to Natural Language Processing (NLP)
Natural Language Processing (NLP) is a subfield of artificial intelligence that enables computers to understand, interpret, and generate human language. It involves the application of computational techniques to analyze text and speech data, allowing machines to perform tasks such as text classification, translation, speech recognition, and sentiment analysis.
NLP combines multiple disciplines, including linguistics, machine learning, deep learning, and computational statistics, to develop models that process and understand natural language. The complexity of human language, including context, grammar, ambiguity, and cultural variations, makes NLP a challenging field that requires advanced algorithms and large-scale data processing.
Modern NLP techniques leverage both rule-based and statistical methods, evolving from simple pattern recognition to complex deep learning models that understand the semantics and syntax of human language. With advancements in neural networks, particularly Transformer architectures like BERT and GPT, NLP systems can generate more accurate, human-like responses, improving applications such as virtual assistants, chatbots, and language translation systems.